Artificial intelligence in quantitative imaging of esophageal cancer: A review on radiomics, sarcopenia, and survival modeling

doi:10.4251/wjgo.v18.i7.119986

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World Journal of Gastrointestinal Oncology

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1948-5204

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastrointest Oncol. Jul 15, 2026; 18(7): 119986
Published online Jul 15, 2026. doi: 10.4251/wjgo.v18.i7.119986

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Figure 1 Conceptual workflow for artificial intelligence-based survival modeling in esophageal cancer. AI: Artificial intelligence; TNM: Tumor-node-metastasis.

Citation: Sathish S, Jain A, Sharma K, Karthika B. Artificial intelligence in quantitative imaging of esophageal cancer: A review on radiomics, sarcopenia, and survival modeling. World J Gastrointest Oncol 2026; 18(7): 119986
URL: https://www.wjgnet.com/1948-5204/full/v18/i7/119986.htm
DOI: https://dx.doi.org/10.4251/wjgo.v18.i7.119986

Sathish S, Jain A, Sharma K, Karthika B. Artificial intelligence in quantitative imaging of esophageal cancer: A review on radiomics, sarcopenia, and survival modeling. World J Gastrointest Oncol 2026; 18(7): 119986 [DOI: 10.4251/wjgo.v18.i7.119986]

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